Abstract
This paper analyzes the yaw data of the 2.5MW wind turbine of XEMC Windpower Company, and the real wind information collected by the wind farm, and proposes a two-level economic model predictive control (TL-EMPC) yaw strategy based on ideal wind measurement by light detection and ranging (LiDAR). This strategy comprehensively considers the power loss caused by yaw misalignment and the structural loads of the yaw bearing during the yaw process, making the yaw system more efficient and economical: In the high wind speed range, the yaw system has a higher sensitivity by setting the threshold of the yaw error angle, so as to fully capture wind energy; in the low wind speed range, fully consider the fatigue load of the critical parts of the wind turbine during the yaw process, thus Improve the economy of the wind turbine yaw system. The fatigue load and limit load of the yaw actuator at different yaw speeds are analyzed, and the best yaw speed is obtained. The finite control set of the yaw speed is established, which is used as the constraint set of the second-level minimum objective function. Finally, an external controller was used to simulate the 2.5MW wind turbine model in Bladed, and the effectiveness of the control strategy was verified.
Highlights
The misalignment angle between the normal direction of the wind turbine rotor plane and the wind direction is called the yaw error angle
This paper proposes the two-level economic model predictive control (TL-economic model predictive control (EMPC)) yaw strategy for the 2.5MW wind turbine of XEMC Windpower Company, and divides the levels according to the wind speed previewed by the light detection and ranging (LiDAR): In the first level, the control strategy of the Controls Advanced Research Turbine 3-Bladed (CART3) turbine is improved, and the yaw threshold is set based on a fixed discrete period which is 30s
By reading the wind file generated in advance, the 90s wind speed and wind direction information at the wind wheel plane can be directly obtained in advance, which can be applied to TL-EMPC
Summary
The misalignment angle between the normal direction of the wind turbine rotor plane and the wind direction is called the yaw error angle. The results of the wind tunnel test conducted by the National Renewable Energy Laboratory (NREL) show that the power of the wind turbine is related to the square of the cosine of the yaw error angle [3]. Misalignment of yaw may lead to an increase in the load of critical parts of the wind turbine. Kragh et al conducted a study on a 5 MW wind turbine and found that yaw misalignment would increase the load on the blade roots, while at low turbulence levels, yaw alignment can reduce blade load by about 20% [5]. An important goal of wind turbine yaw controller is to increase power generation and reduce fatigue loads on wind turbine components
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